Spectral and Energy Spectral Efficiency Optimization of Joint Transmit and Receive Beamforming Based Multi-Relay MIMO-OFDMA Cellular Networks

被引:28
作者
Cheung, Kent Tsz Kan [1 ]
Yang, Shaoshi [1 ]
Hanzo, Lajos [1 ]
机构
[1] Univ Southampton, Sch Elect & Comp Sci, Southampton SO17 1BJ, Hants, England
基金
英国工程与自然科学研究理事会; 欧洲研究理事会;
关键词
Green communications; spatial multiplexing; beamforming; multi-relay; multiple-input-multiple-output orthogonal frequency-division multiple-access (MIMO-OFDMA); fractional programming; dual decomposition; cross-layer design; RESOURCE-ALLOCATION; SYSTEMS; CAPACITY; DIAGONALIZATION; DOWNLINK;
D O I
10.1109/TWC.2014.2348996
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We first conceive a novel transmission protocol for a multi-relay multiple-input-multiple-output orthogonal frequency-division multiple-access (MIMO-OFDMA) cellular network based on joint transmit and receive beamforming. We then address the associated network-wide spectral efficiency (SE) and energy spectral efficiency (ESE) optimization problems. More specifically, the network's MIMO channels are mathematically decomposed into several effective multiple-input-single-output (MISO) channels, which are essentially spatially multiplexed for transmission. Hence, these effective MISO channels are referred to as spatial multiplexing components (SMCs). For the sake of improving the SE/ESE performance attained, the SMCs are grouped using a pair of proposed grouping algorithms. The first is optimal in the sense that it exhaustively evaluates all the possible combinations of SMCs satisfying both the semi-orthogonality criterion and other relevant system constraints, whereas the second is a lower-complexity alternative. Corresponding to each of the two grouping algorithms, the pair of SE and ESE maximization problems are formulated, thus the optimal SMC groups and optimal power control variables can be obtained for each subcarrier block. These optimization problems are proven to be concave, and the dual decomposition approach is employed for obtaining their solutions. Relying on these optimization solutions, the impact of various system parameters on both the attainable SE and ESE is characterized. In particular, we demonstrate that under certain conditions the lower-complexity SMC grouping algorithm achieves 90% of the SE/ESE attained by the exhaustive-search based optimal grouping algorithm, while imposing as little as 3.5% of the latter scheme's computational complexity.
引用
收藏
页码:6147 / 6165
页数:19
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